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Correlation propagation for uncertainty analysis of structures based on a non-probabilistic ellipsoidal model.
- Source :
-
Applied Mathematical Modelling . Dec2020, Vol. 88, p190-207. 18p. - Publication Year :
- 2020
-
Abstract
- • Correlation propagation method is proposed to obtain the uncertain responses domain. • The ME model is utilized to quantify the uncertainties in parameters and responses. • Subinterval decomposition analysis method is adopted to evaluate response intervals. • The non-probabilistic correlation propagation equations are theoretically derived. • The propagated correlations are completely accurate for the second-order systems. Traditional non-probabilistic methods for uncertainty propagation problems evaluate only the lower and upper bounds of structural responses, lacking any analysis of the correlations among the structural multi-responses. In this paper, a new non-probabilistic correlation propagation method is proposed to effectively evaluate the intervals and non-probabilistic correlation matrix of the structural responses. The uncertainty propagation process with correlated parameters is first decomposed into an interval propagation problem and a correlation propagation problem. The ellipsoidal model is then utilized to describe the uncertainty domain of the correlated parameters. For the interval propagation problem, a subinterval decomposition analysis method is developed based on the ellipsoidal model to efficiently evaluate the intervals of responses with a low computational cost. More importantly, the non-probabilistic correlation propagation equations are newly derived for theoretically predicting the correlations among the uncertain responses. Finally, the multi-dimensional ellipsoidal model is adopted again to represent both uncertainties and correlations of multi-responses. Three examples are presented to examine the accuracy and effectiveness of the proposed method both numerically and experimentally. [ABSTRACT FROM AUTHOR]
- Subjects :
- *UNCERTAINTY
*DECOMPOSITION method
*STATISTICAL correlation
Subjects
Details
- Language :
- English
- ISSN :
- 0307904X
- Volume :
- 88
- Database :
- Academic Search Index
- Journal :
- Applied Mathematical Modelling
- Publication Type :
- Academic Journal
- Accession number :
- 145477217
- Full Text :
- https://doi.org/10.1016/j.apm.2020.06.009